Package index • sysPrep

Deduplication

ESSENCE data frequently contains multiple rows for the same visit due to data feed retransmissions, midnight-crossing date changes, patient identifier corrections, and patient class transitions. These functions identify, characterize, and remove duplicate records that would otherwise inflate case counts or create false-positive clusters.

dedupe(): Remove duplicate records from an ESSENCE data pull
summarize_duplicates(): Summarize duplicate records in an ESSENCE data pull
classify_duplicates(): Classify the mechanism of duplication in an ESSENCE data pull

Care Setting Quality Assurance

The ESSENCE API returns all facilities that submitted matching records, including non-emergency providers (primary care clinics, specialty practices). Free-standing emergency departments (FSEDs) may be onboarded with a FacilityType of “Urgent Care” – one of two valid ESSENCE facility type assignments for FSEDs – which prevents front-end API filtering by facility type from correctly identifying them as emergency providers. These functions filter to valid care settings, correct known facility type assignments before filtering, and flag facilities with anomalous visit volumes.

filter_care_setting(): Filter ESSENCE data to valid emergency and inpatient care settings
review_facility_ed_visits(): Review facility ED visit counts for data quality assessment

Encounter Linkage

A row showing HasBeenAdmitted = 1 and HasBeenE = 0 can mean either a genuine direct admission or a mis-submitted ED-to-inpatient continuity break reported as two unrelated records – nothing in a single row tells you which. The former is invisible to HasBeenE = 1 queries; the latter double-counts a single encounter if left unlinked. link_encounters() links ED and inpatient records into unified care episodes, correcting both problems at once.

link_encounters(): Link ED and inpatient admission records into unified care episodes

Geographic Attribution

ESSENCE records include out-of-state residents and visits with unknown residential geography (OTHER_REGION). Discarding these visits systematically understates burden at facilities serving cross-border populations and can exclude real visits from cluster/anomaly detection scoped to the treating facility’s county. assign_treating_geography() implements a hybrid approach – preserving residential geography for in-state patients while reassigning only out-of-state and OTHER_REGION visits to the treating facility’s county. assign_facility_geography() applies full incidence-at-location reassignment, attributing all visits to the treating facility’s geography regardless of patient origin. Both write to new columns by default (region_hybrid/region_facility), leaving the original Region/ZipCode untouched, so calling either – or both, chained – is always safe to try and safe to re-run.

assign_treating_geography(): Assign treating facility geography to out-of-state and OTHER_REGION visits
assign_facility_geography(): Assign facility geography to all visits for incidence-at-location analysis

Data

Synthetic example datasets demonstrating common ESSENCE data quality issues. All data are fully fabricated with no real patient, facility, or geographic identifiers.

essence_raw: Synthetic raw ESSENCE-like ED visit data
essence_clean: Synthetic cleaned ESSENCE-like ED visit data
essence_ed_raw: Synthetic raw ESSENCE-like ED pull for encounter linkage
essence_inp_raw: Synthetic raw ESSENCE-like inpatient admission pull for encounter linkage